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In this work, a nonlinear programming (NLP) model is formulated for the design of selective effluent treatment systems containing traces of amoxicillin. The presence of antibiotic in surface water bodies or groundwater generates an important environmental problem due to its bio-accumulative potential and the development of antibiotic resilient bacteria. Current methods employed in the removal of drugs and antibiotics include chemical oxidation by Fenton reagents, flocculation and photochemical treatments. However, their removal efficiencies are still limited and studies are required for the optimization of the treatment costs. An electrochemical technology is incorporated in the system for the degradation of amoxicillin. The NLP model developed is built from a basic network superstructure that expands the space of alternative treatment possibilities, minimizing the total flowrate that is sent to treatment. Four illustrative examples are solved to show the versatility and usefulness of the model proposed.

Modelo de Programación No Lineal para el Diseño de Sistemas de Tratamiento Electroquímico de Aguas Residuales Contaminadas con Trazas de Amoxicilina